本文介绍了一种利用纯文本数据增强语音识别模型的新方法。该研究侧重于编码器主导的架构，证明了更大的编码器与更小的解码器配对可以实现与具有更大解码器的模型相当或更好的性能。研究发现，像随机时长模型这样的简单配置通常优于更复杂的方法，从而简化了训练过程。所有相关的代码和实验设置均已公开发布。 AI
影响 提出了一个简化的语音识别模型训练流程，可能降低研究人员和开发者的入门门槛。
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arXiv:2604.26514v1 Announce Type: new Abstract: This paper investigates efficient methods for utilizing text-only data to improve speech recognition, focusing on encoder-dominated models that facilitate faster recognition. We provide a comprehensive comparison of techniques to in…
This paper investigates efficient methods for utilizing text-only data to improve speech recognition, focusing on encoder-dominated models that facilitate faster recognition. We provide a comprehensive comparison of techniques to integrate text-only data, including modality match…
This paper investigates efficient methods for utilizing text-only data to improve speech recognition, focusing on encoder-dominated models that facilitate faster recognition. We provide a comprehensive comparison of techniques to integrate text-only data, including modality match…